####
#### Eroll Kuhn & Rahsaan Maxwell
#### Generating Histograms of two outcome variables
#### 02.26.2020
rm(list=ls())
# read in frame
df <- read.csv("/Users/erollkuhn/Dropbox (Personal)/Refugee Context Project/Clean Code V5/3.Outcomes Descriptive/Output/Tables/Combined_Tables.csv")
# pre-processing
df <- data.frame(df)
## outcome subsets and recode outcome
df_factor <- subset(df,df$Outcome=="Factor")
df_factor_weighted <- subset(df,(df$Outcome=="Factor" & df$Type=="Weighted"))
## index
df_index <- subset(df,df$Outcome=="Index")
df_index_weighted <- subset(df,(df$Outcome=="Index" & df$Type=="Weighted"))
rm(df)
## plot
library(ggplot2)
cbPalette <- c("#E69F00", "#56B4E9", "#009E73", "#F0E442", "#0072B2", "#D55E00", "#CC79A7", "#000000")
###############
#index
setwd("/Users/erollkuhn/Dropbox (Personal)/Refugee Context Project/Clean Code V4/3.Outcomes Descriptive/Output/Figures")
png("index_histogram_both.png",
width=10,height=6,units='in',res=300)
ggplot(data = df_index, aes(y = as.numeric(Prop),
x=as.numeric(Numeric))) +
geom_col() +
facet_wrap(~Type) +
xlab("Welcomeness Index") +
ylab("Proportion of Responses") +
theme_bw() +
theme(legend.direction = "horizontal",
legend.position = "bottom",
panel.grid.major.x = element_blank(),
panel.grid.minor = element_blank(),
panel.grid.major.y = element_line(size = .15, linetype = 2, color = "gray75"))
dev.off()
png("index_histogram_weightedOnly.png",
width=10,height=6,units='in',res=300)
ggplot(data = df_index_weighted, aes(y = as.numeric(Prop),
x=as.numeric(Numeric))) +
geom_col() +
facet_wrap(~Type) +
xlab("Welcomeness Index") +
ylab("Proportion of Responses") +
theme_bw() +
theme(legend.direction = "horizontal",
legend.position = "bottom",
panel.grid.major.x = element_blank(),
panel.grid.minor = element_blank(),
panel.grid.major.y = element_line(size = .15, linetype = 2, color = "gray75"))
dev.off()
###########################
# factor
png("factor_histogram_both.png",
width=10,height=6,units='in',res=300)
ggplot(data = df_factor, aes(y = as.numeric(Prop),
x=as.numeric(Numeric))) +
geom_col(width =0.005) +
facet_wrap(~Type) +
xlab("Welcomeness Factor") +
ylab("Proportion of Responses") +
theme_bw() +
theme(legend.direction = "horizontal",
legend.position = "bottom",
panel.grid.major.x = element_blank(),
panel.grid.minor = element_blank(),
panel.grid.major.y = element_line(size = .15, linetype = 2, color = "gray75"))
dev.off()
png("factor_histogram_weighted.png",
width=10,height=6,units='in',res=300)
ggplot(data = df_factor_weighted, aes(y = as.numeric(Prop),
x=as.numeric(Numeric))) +
geom_col(width =0.005) +
facet_wrap(~Type) +
xlab("Welcomeness Factor") +
ylab("Proportion of Responses") +
theme_bw() +
theme(legend.direction = "horizontal",
legend.position = "bottom",
panel.grid.major.x = element_blank(),
panel.grid.minor = element_blank(),
panel.grid.major.y = element_line(size = .15, linetype = 2, color = "gray75"))
dev.off()
####
#### Eroll Kuhn & Rahsaan Maxwell
#### Generating Histograms of two outcome variables
#### 02.26.2020
rm(list=ls())
# read in frame
df <- read.csv("/Users/erollkuhn/Dropbox (Personal)/Refugee Context Project/Clean Code V5/3.Outcomes Descriptive/Output/Tables/Combined_Tables.csv")
# pre-processing
df <- data.frame(df)
## outcome subsets and recode outcome
df_factor <- subset(df,df$Outcome=="Factor")
df_factor_weighted <- subset(df,(df$Outcome=="Factor" & df$Type=="Weighted"))
## index
df_index <- subset(df,df$Outcome=="Index")
df_index_weighted <- subset(df,(df$Outcome=="Index" & df$Type=="Weighted"))
rm(df)
## plot
library(ggplot2)
cbPalette <- c("#E69F00", "#56B4E9", "#009E73", "#F0E442", "#0072B2", "#D55E00", "#CC79A7", "#000000")
###############
#index
setwd("/Users/erollkuhn/Dropbox (Personal)/Refugee Context Project/Clean Code V5/3.Outcomes Descriptive/Output/Figures")
png("index_histogram_both.png",
width=10,height=6,units='in',res=300)
ggplot(data = df_index, aes(y = as.numeric(Prop),
x=as.numeric(Numeric))) +
geom_col() +
facet_wrap(~Type) +
xlab("Welcomeness Index") +
ylab("Proportion of Responses") +
theme_bw() +
theme(legend.direction = "horizontal",
legend.position = "bottom",
panel.grid.major.x = element_blank(),
panel.grid.minor = element_blank(),
panel.grid.major.y = element_line(size = .15, linetype = 2, color = "gray75"))
dev.off()
png("index_histogram_weightedOnly.png",
width=10,height=6,units='in',res=300)
ggplot(data = df_index_weighted, aes(y = as.numeric(Prop),
x=as.numeric(Numeric))) +
geom_col() +
facet_wrap(~Type) +
xlab("Welcomeness Index") +
ylab("Proportion of Responses") +
theme_bw() +
theme(legend.direction = "horizontal",
legend.position = "bottom",
panel.grid.major.x = element_blank(),
panel.grid.minor = element_blank(),
panel.grid.major.y = element_line(size = .15, linetype = 2, color = "gray75"))
dev.off()
###########################
# factor
png("factor_histogram_both.png",
width=10,height=6,units='in',res=300)
ggplot(data = df_factor, aes(y = as.numeric(Prop),
x=as.numeric(Numeric))) +
geom_col(width =0.005) +
facet_wrap(~Type) +
xlab("Welcomeness Factor") +
ylab("Proportion of Responses") +
theme_bw() +
theme(legend.direction = "horizontal",
legend.position = "bottom",
panel.grid.major.x = element_blank(),
panel.grid.minor = element_blank(),
panel.grid.major.y = element_line(size = .15, linetype = 2, color = "gray75"))
dev.off()
png("factor_histogram_weighted.png",
width=10,height=6,units='in',res=300)
ggplot(data = df_factor_weighted, aes(y = as.numeric(Prop),
x=as.numeric(Numeric))) +
geom_col(width =0.005) +
facet_wrap(~Type) +
xlab("Welcomeness Factor") +
ylab("Proportion of Responses") +
theme_bw() +
theme(legend.direction = "horizontal",
legend.position = "bottom",
panel.grid.major.x = element_blank(),
panel.grid.minor = element_blank(),
panel.grid.major.y = element_line(size = .15, linetype = 2, color = "gray75"))
dev.off()
